Data visualization (DataViz) libraries play a crucial role in presentation, data analysis, and application development, underscoring the importance of their accuracy in transforming data into visual representations. Incorrect visualizations can adversely impact user experience, distort information conveyance, and influence user perception and decision-making processes. Visual bugs in these libraries can be particularly insidious as they may not cause obvious errors like crashes, but instead mislead users of the underlying data graphically, resulting in wrong decision making. Consequently, a good understanding of the unique characteristics of bugs in DataViz libraries is essential for researchers and developers to detect and fix bugs in DataViz libraries.
This study presents the first comprehensive analysis of bugs in DataViz libraries, examining 564 bugs collected from five widely-used libraries. Our study systematically analyzes their symptoms and root causes, and provides a detailed taxonomy. We found that incorrect/inaccurate plots are pervasive in DataViz libraries and incorrect graphic computation is the major root cause, which necessitates further automated testing methods for DataViz libraries. Moreover, we identified eight key steps to trigger such bugs and two test oracles specific to DataViz libraries, which may inspire future research in designing effective automated testing techniques. Furthermore, with the recent advancements in Vision Language Models (VLMs), we explored the feasibility of applying these models to detect incorrect/inaccurate plots. The results show that the effectiveness of VLMs in bug detection varies from 29% to 57%, depending on the prompts, and adding more information in prompts does not necessarily increase the effectiveness. Our findings offer valuable insights into the nature and patterns of bugs in DataViz libraries, providing a foundation for developers and researchers to improve library reliability, and ultimately benefit more accurate and reliable data visualizations across various domains.
Wed 25 JunDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
11:00 - 12:30 | |||
11:00 20mTalk | ChatDBG: Augmenting Debugging with Large Language Models Research Papers Kyla H. Levin University of Massachusetts Amherst, USA, Nicolas van Kempen University of Massachusetts Amherst, USA, Emery D. Berger University of Massachusetts Amherst and Amazon Web Services, Stephen N. Freund Williams College DOI Pre-print | ||
11:20 10mTalk | Towards Adaptive Software Agents for Debugging Ideas, Visions and Reflections Yacine Majdoub IReSCoMath Research Lab, Faculty of Sciences, University Of Gabes, Tunisia, Eya Ben Charrada IReSCoMath Research Lab, Faculty of Sciences, University Of Gabes, Tunisia, Haifa Touati IReSCoMath Research Lab, Faculty of Sciences, University Of Gabes, Tunisia Pre-print | ||
11:30 20mTalk | Empirically Evaluating the Impact of Object-Centric Breakpoints on the Debugging of Object-Oriented Programs Research Papers Valentin Bourcier INRIA, Pooja Rani University of Zurich, Maximilian Ignacio Willembrinck Santander Univ. Lille, Inria, CNRS, Centrale Lille, UMR 9189 CRIStAL F-59000 Lille, France, Alberto Bacchelli University of Zurich, Steven Costiou INRIA Lille DOI | ||
11:50 20mTalk | An Empirical Study of Bugs in Data Visualization Libraries Research Papers Weiqi Lu The Hong Kong University of Science and Technology, Yongqiang Tian , Xiaohan Zhong The Hong Kong University of Science and Technology, Haoyang Ma Hong Kong University of Science and Technology, Zhenyang Xu University of Waterloo, Shing-Chi Cheung Hong Kong University of Science and Technology, Chengnian Sun University of Waterloo DOI | ||
12:10 20mTalk | DuoReduce: Bug Isolation for Multi-Layer Extensible Compilation Research Papers Jiyuan Wang University of California at Los Angeles, Yuxin Qiu University of California at Riverside, Ben Limpanukorn University of California, Los Angeles, Hong Jin Kang University of Sydney, Qian Zhang University of California at Riverside, Miryung Kim UCLA and Amazon Web Services DOI Pre-print | ||